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A Penalisation-Based Ranking Approach for the Mixed Monolingual Task of WebCLEF 2006

机译:基于惩罚的惩罚排名方法,用于Webclef 2006的混合单格式任务

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This paper presents an approach of a cross-lingual information retrieval which uses a ranking method based on a penalisation version of the Jaccard formula. The obtained results after the submission of a set of runs to the WebCLEF 2006 have shown that this simple ranking formula may be used in a cross-lingual environment. A comparison with runs submitted by other teams ranks us in a third place by using all the topics. A fourth place is obtained with our best overall results by using only the new topic set, and a second place was got by using only the automatic topics of the new topic set. An exact comparison with the rest of the participants is in fact difficult to obtain and, therefore, we consider that further detailed analysis of the components should be done in order to determine the best components of the proposed system.
机译:本文提出了一种跨语言信息检索的方法,它使用基于Jaccard公式的惩罚版本的排名方法。在提交到WebClef 2006之后的所获得的结果已经表明,该简单排名公式可用于交叉环境。与其他团队提交的运行的比较通过使用所有主题在第三名中排名我们。使用我们仅使用新主题集的最佳总体结果获得第四位,并且仅使用新主题集的自动主题来获得第二个地方。事实上,与参与者的其余部分进行了完全的比较难以获得,因此,我们认为应该进行对组件的进一步详细分析,以便确定所提出的系统的最佳组成部分。

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